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To automate a full software engineering workflow, you can use a skill that orchestrates planning, code generation, review, and testing. It executes these stages autonomously to handle the entire software development lifecycle for a feature or task.

An autonomous engineering workflow is a process where AI orchestrates specialized skills to manage software development. It handles coding tasks by automatically deepening the initial plan, generating code, resolving todos, and executing tests.

Yes, you can integrate task completion skills into your autonomous code generation and review process. The workflow supports integration with optional specialized skills like 'ralph-wiggum' to facilitate task completion and compound engineering tool execution.

No, you do not need to install mandatory dependencies to run an end-to-end automated software development lifecycle. The workflow operates independently but supports optional integration with other specialized skills for enhanced execution.

The best way to kickstart new feature development is to trigger an autonomous engineering workflow. It manages the entire lifecycle by autonomously planning the feature, writing the code, running tests, and preparing the output for human review.